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Connected and Automated Vehicles

Modern day Connected and Automated Vehicles (CAV) serve as exemplars of distributed, networked Cyber-Physical Systems-of-Systems (CPS) with immense diversity, scale, scope and complexity. Our CAV faculty’s research activities explore various facets of design, modeling, analysis, control and validation of distributed and networked cyber-physical systems (small- to full-scale vehicles, energy systems, EVs, HEVs, robotics/automation) in numerous application arenas. Our unique and innovative research blends computational/virtual-prototyping approaches (digital-twins, visualization, data-fusion, data-science and artificial-intelligence) with embodiment/physical-prototyping approaches (nonlinear estimation & control, mechatronic realization, verification & validation) to further the cyber-physical system paradigm. Research activities explore the use of cutting-edge techniques from multi-body dynamics, non-linear estimation and control, data-augmentation & artificial intelligence, high-performance compute, X-in-the-loop (XIL; X = software/hardware at component, subsystem, system, system-of-systems) to support these efforts.

  • Onroad/offroad deployments by complexity
  • Manufacturing deployments by complexity

Automotive engineering students who select Connected and Automated Vehicles for their technical track will participate in a number of academic and research activities related to conceiving, prototyping, deploying, and validating such CAVs across varying physical scales and operational design domains with applications in on-road, off-road, and manufacturing shop-floor settings.

Team

Dr. Venkat Krovi
Connected Autonomous Vehicle (CAV) systems-of-systems, Distributed multi-scale human-autonomy synergy; Applications for on-road, off-road and manufacturing shop-floor applications; lifecycle treatment of human- and hardware-in-the-loop systems-of-systems

Dr. Beshah Ayalew
Vehicle dynamics modeling and control; Predictive and coordinated control of multi-lane traffic; Multi-target multi-sensor tracking; Collaborative situational awareness in connected traffic; Information fusion; use of these in Advanced Driver Assistance Systems (ADAS)

Dr. Yunyi Jia
Automated vehicles (perception, modeling, controls and learning); modeling, planning and controls of connected and mixed vehicles; human-vehicle interactions; human factors and user acceptance of automated vehicles; advanced sensing systems for automated vehicles and human-vehicle interactions

Dr. Bing Li
Sensors; electromagnetic; signal/imaging processing; sensor fusion; high-performance computing; modeling and optimization; computer vision; perception; machine/deep learning; robotics; SLAM; robotic inspections; assistive technologies; autonomy

Dr. Pierluigi Pisu
Secure Control for Cyberphysical Systems, Functional Safety, Cooperation and Energy Management, Machine learning approaches and Resilient Control, VR simulation and validation

Dr. Matthias Schmid
Advanced estimation and control techniques, uncertainty propagation, sensor fusion, mathematical frameworks, stochastic differential equations, perception, prediction

Please visit the individual links below to get further details on ongoing research projects, publications, undergraduate- and graduate-student researchers, and outreach activities.

Krovi: Automation Robotics and Mechatronics Lab (ARMLAB)

Jia: Collaborative Robotics and Automation (CRA) Lab

Schmid: Dynamics Estimation and Control Lab

Ayalew: Applied Dynamics and Control Group

Pisu: Diagnostics and Cybersecurity of Connected Vehicles


FACILITIES